首页> 外文会议>International Instrumentation and Measurement Technology Conference >Use of phantoms and test objects for local dynamic range evaluation in medical ultrasounds: A preliminary study
【24h】

Use of phantoms and test objects for local dynamic range evaluation in medical ultrasounds: A preliminary study

机译:体模和测试对象在医学超声中用于局部动态范围评估的初步研究

获取原文

摘要

In the ultrasound image the relationship between echo amplitudes and gray levels is expressed by means of the Grayscale Mapping Function (GMF), that is the greyscale transfer function associated with the echo displayed. The GMF allows the determination of some image quality parameters and quantities, among which the Local Dynamic Range (LDR) is relevant, since it is defined as the 20·log10 of the ratio of the minimum echo amplitude that yields the maximum grey level in the digitized image to that of the echo that yields the lowest grey level at the same location in the image and the same settings. This study reports the implementation of a method for the automatic determination of the LDR on medical ultrasound scanners and its application by means of a commercial grayscale ultrasound phantom, nevertheless it can be used also with general purpose phantoms: the LDR is obtained from the estimation of the GMF, based on processing of a sequence of uncompressed bidimensional ultrasound images provided by the scanner. In the manuscript, some theoretical considerations have been done to determine the GMF and its fitting model, as well as the LDR values, after that an experimental setup is described and some results are shown for an ultrasound system equipped with two different probes.
机译:在超声图像中,回声幅度和灰度级之间的关系通过灰度映射函数(GMF)表示,该函数是与显示的回声关联的灰度传递函数。 GMF可以确定一些图像质量参数和数量,其中与本地动态范围(LDR)相关,因为它被定义为最小回波振幅比的20·log10,从而在图像中产生最大灰度。数字化的图像与在图像中相同位置和相同设置下产生最低灰度级的回波图像相同。这项研究报告了一种在医学超声扫描仪上自动确定LDR的方法的实施方法,以及通过商业灰度超声体模对其进行应用的方法,尽管如此,它也可以与通用体模一起使用:LDR是从对LDR的估计中获得的。 GMF,基于对扫描仪提供的一系列未压缩二维超声图像的处理。在手稿中,已经进行了一些理论上的考虑来确定GMF及其拟合模型以及LDR值,然后描述了实验装置并显示了配备两个不同探头的超声系统的一些结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号